uar1 surrogates

pyleoclim/core/coherence.py

@@ -692,17 +692,17 @@ def signif_test(self, number=200, method='ar1sim', seed=None, qs=[0.95], setting
 
             coh.signif_test(method='phaseran').plot() 
         '''
-
+        from ..core.surrogateseries import SurrogateSeries
+
         if number == 0:
             return self
 
         new = self.copy()
-        surr1 = self.timeseries1.surrogates(
-            number=number, seed=seed, method=method, settings=settings
-        )
-        surr2 = self.timeseries2.surrogates(
-            number=number, seed=seed, method=method, settings=settings
-        )
+
+        surr1 = SurrogateSeries(method=method,number=number, seed=seed)
+        surr1.from_series(self.timeseries1)
+        surr2 = SurrogateSeries(method=method,number=number, seed=seed)
+        surr2.from_series(self.timeseries2)
 
         # adjust time axis
 
@@ -730,11 +730,6 @@ def signif_test(self, number=200, method='ar1sim', seed=None, qs=[0.95], setting
         wtc_qs = np.ndarray(shape=(nq, nf, nt))
         xwt_qs = np.empty_like(wtc_qs)
 
-        # for i in range(nf):
-        #     for j in range(nt):
-        #         wtc_qs[:,i,j] = mquantiles(wtcs[:,i,j], qs)
-        #         xwt_qs[:,i,j] = mquantiles(xwts[:,i,j], qs)
-
         # extract quantiles and reshape
         wtc_qs = mquantiles(wtcs_r, qs, axis=0)
         wtc_qs = np.reshape(wtc_qs, (nq, nf, nt))

pyleoclim/core/ensembleseries.py

@@ -22,8 +22,6 @@
 import matplotlib.transforms as transforms
 import matplotlib as mpl
 from tqdm import tqdm
-#import warnings
-#from scipy.stats.mstats import mquantiles
 
 class EnsembleSeries(MultipleSeries):
     ''' EnsembleSeries object
@@ -524,6 +522,8 @@ def plot_traces(self, figsize=[10, 4], xlabel=None, ylabel=None, title=None, num
             '''
         savefig_settings = {} if savefig_settings is None else savefig_settings.copy()
         lgd_kwargs = {} if lgd_kwargs is None else lgd_kwargs.copy()
+
+        num_traces = min(num_traces, len(self.series_list)) # restrict to the smaller of the two
 
         # generate default axis labels
         time_label, value_label = self.make_labels()
@@ -972,7 +972,7 @@ def histplot(self, figsize=[10, 4], title=None, savefig_settings=None,
                  ax=None, ylabel='KDE', vertical=False, edgecolor='w', **plot_kwargs):
         """ Plots the distribution of the timeseries across ensembles
 
-        Reuses seaborn [histplot](https://seaborn.pydata.org/generated/seaborn.histplot.html) function.
+        Reuses the seaborn [histplot](https://seaborn.pydata.org/generated/seaborn.histplot.html) function.
 
         Parameters
         ----------

pyleoclim/core/psds.py

@@ -1,10 +1,6 @@
 from ..utils import plotting
 from ..utils import wavelet as waveutils
 from ..utils import spectral as specutils
-#from ..utils import tsbase
-
-#from ..core.multiplepsd import *
-#import ..core.multiplepsd
 
 
 import matplotlib.pyplot as plt
@@ -16,28 +12,6 @@
 
 from matplotlib.ticker import ScalarFormatter, FormatStrFormatter
 
-
-# def infer_period_unit_from_time_unit(time_unit):
-#     ''' infer a period unit based on the given time unit
-
-#     '''
-#     if time_unit is None:
-#         period_unit = None
-#     else:
-#         unit_group = lipdutils.timeUnitsCheck(time_unit)
-#         if unit_group != 'unknown':
-#             if unit_group == 'kage_units':
-#                 period_unit = 'kyrs'
-#             else:
-#                 period_unit = 'yrs'
-#         else:
-#             if time_unit[-1] == 's':
-#                 period_unit = time_unit
-#             else:
-#                 period_unit = f'{time_unit}s'
-
-#     return period_unit
-
 def infer_period_unit_from_time_unit(time_unit):
     ''' infer a period unit based on the given time unit
 
@@ -273,6 +247,7 @@ def signif_test(self, method='ar1sim', number=None, seed=None, qs=[0.95],
         pyleoclim.core.series.Series.wavelet : Performs wavelet analysis on Pyleoclim Series
 
         '''
+        from ..core.surrogateseries import SurrogateSeries
 
         if self.spec_method == 'wwz' and method == 'ar1asym':
             raise ValueError('Asymptotic solution is not supported for the wwz method')
@@ -300,10 +275,9 @@ def signif_test(self, method='ar1sim', number=None, seed=None, qs=[0.95],
                 return self
 
             new = self.copy()
-            surr = self.timeseries.surrogates(
-                number=number, seed=seed, method=method, settings=settings
-            )
-
+            surr = SurrogateSeries(method=method,number=number, seed=seed)
+            surr.from_series(self.timeseries)
+
             if signif_scals:
                 surr_psd = surr.spectral(
                     method=self.spec_method, settings=self.spec_args, scalogram_list=signif_scals

pyleoclim/core/scalograms.py

@@ -482,6 +482,7 @@ def signif_test(self, method='ar1sim', number=None, seed=None, qs=[0.95],
             scalogram = ts.wavelet().signif_test(number=2, export_scal=True)
 
         '''
+
         if self.wave_method == 'wwz' and method == 'ar1asym':
             raise ValueError('Asymptotic solution is not supported for the wwz method')
 
@@ -490,6 +491,7 @@ def signif_test(self, method='ar1sim', number=None, seed=None, qs=[0.95],
                 raise ValueError(f"The available methods are: {acceptable_methods}")
 
         if method in ['ar1sim','uar1'] :
+            from ..core.surrogateseries import SurrogateSeries
 
             if hasattr(self,'signif_scals'):
                 signif_scals = self.signif_scals
@@ -517,14 +519,14 @@ def signif_test(self, method='ar1sim', number=None, seed=None, qs=[0.95],
                     number -= len(scalogram_list)
                     surr_scal_tmp = []
                     surr_scal_tmp.extend(scalogram_list)
-                    surr = self.timeseries.surrogates(number=number, seed=seed,
-                                                      method=method, settings=settings)
+                    surr = SurrogateSeries(method=method,number=number, seed=seed)
+                    surr.from_series(self.timeseries)
 
                     surr_scal_tmp.extend(surr.wavelet(method=self.wave_method, settings=self.wave_args).scalogram_list)
                     surr_scal = MultipleScalogram(scalogram_list=surr_scal_tmp)
             else:
-                surr = self.timeseries.surrogates(number=number, seed=seed,
-                                                  method=method, settings=settings)
+                surr = SurrogateSeries(method=method,number=number, seed=seed)
+                surr.from_series(self.timeseries)
                 surr_scal = surr.wavelet(method=self.wave_method, settings=self.wave_args)
 
             if type(qs) is not list: